Owing to their complimentary characteristics, global positioning system (GPS) and inertial navigation system (INS) are integrated,\r\ntraditionally through Kalman filter (KF), to obtain improved navigational solution. To reduce the overall cost of the system,\r\nmicroelectromechanical system- (MEMS-) based INS is utilized. One of the approaches is to reduce the number of low-cost\r\ninertial sensors, decreasing their error contribution which leads to a reduced inertial sensor system (RISS). This paper uses KF\r\nto integrate GPS and 3D RISS in a loosely coupled fashion to enhance navigational solution while further improvement is achieved\r\nby augmenting it with map matching (MM). The 3D RISS consists of only one gyroscope and two accelerometers along with the\r\nvehicle�s built-in odometer. MM limits the error growth during GPS outages by restricting the predicted positions to the road\r\nnetworks. The performance of proposed method is compared with KF-only 3D RISS/GPS integration to demonstrate the efficacy\r\nof the proposed technique.
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